基于改进模糊数量化理论的事故微观预测模型  

Micro Prediction Model of Traffic Accident Based on Improved Fuzzy Quantitative Theory

作　　者：秦利燕[1] 秦玉权[2] 邵春福[3] 

机构地区：[1]山东交通学院,山东济南250023 [2]山东交通职业学院,山东潍坊261206 [3]北京交通大学交通运输学院,北京100044

出　　处：《公路交通科技》2012年第6期105-109,共5页Journal of Highway and Transportation Research and Development

基　　金：国家重点基础研究发展计划(九七三计划)项目(2006CB705500);山东省自然科学基金项目(ZR2011GM013);山东交通学院自然基金项目(Z201013)

摘　　要：针对道路交通事故发生的随机性及影响事故发生的因素很多,而且影响因素中既有定量因素又有定性因素的情况。首先分析了道路交通事故事故4项指标和事故率,确定事故率作为微观预测目标;然后从人-车-路组成的系统观点出发对事故因素分析,选取驾驶员的驾龄、车道数、平曲线半径、纵坡度、路面情况、路口路段类型、道路宽度和交通流量等变量作为主要影响因素,其中前7项作为定性影响因素,交通流量作为定量影响因素,各定性因素下分为若干类目;最后在数量化理论的基础之上建立了改进的模糊道路交通事故微观预测模型。该模型以某国道466.678～559.792 km段作为算例进行计算,计算结果表明:三枝交叉口对事故影响最大,针对该路段提出具体的道路整改意见。The random feature of traffic accidents with multiple influencing factors includes qualitative and quantitative ones. The accident rate was selected as the microscopic prediction objective after analyzing 4 traffic accident indexes and accident rates. Then several factors, including driving years, number of lanes, radius of horizontal curve, longitudinal grade, road surface status, types of intersection and road section, width of road surface and traffic volume were selected as major influencing factors for analyzing the influencing factors from a systematic perspective with the combination of human, vehicle and road. Among these factors, traffic volume was quantative factor, and the other were qualitative factors which were divided into several categories respectively. An improved fuzzy microscopic model for predicting traffic accidents was established based on quantitative theory. To verify the model, the data of road accidents and a 466. 678 - 559. 792 km section on certain national highway was taken for example calculation. The calculation result indicates that three-way intersection has the greatest influence on road accidents. Moreover, some proposals were put forward to improve the present road condition of the selected road section.

关 键 词：交通工程 道路安全 改进的模糊数量化理论 微观预测 道路交通事故 

分 类 号：U491.31[交通运输工程—交通运输规划与管理]